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      Abortion decision-making process trajectories and determinants in low- and middle-income countries: A mixed-methods systematic review and meta-analysis

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          Summary

          Background

          About 45.1% of all induced abortions are unsafe and 97% of these occur in low- and middle-income countries (LMICs). Women's abortion decisions may be complex and are influenced by various factors. We aimed to delineate women's abortion decision-making trajectories and their determinants in LMICs.

          Methods

          We searched Medline, EMBASE, PsychInfo, Global Health, Web of Science, Scopus, IBSS, CINAHL, WHO Global Index Medicus, the Cochrane Library, WHO website, ProQuest, and Google Scholar for primary studies and reports published between January 1, 2000, and February 16, 2021 (updated on June 06, 2022), on induced abortion decision-making trajectories and/or their determinants in LMICs. We excluded studies on spontaneous abortion. Two independent reviewers extracted and assessed quality of each paper. We used “best fit” framework synthesis to synthesise abortion decision-making trajectories and thematic synthesis to synthesise their determinants. We analysed quantitative findings using random effects model. The study protocol is registered with PROSPERO number CRD42021224719.

          Findings

          Of the 6960 articles identified, we included 79 in the systematic review and 14 in the meta-analysis. We identified nine abortion decision-making trajectories: pregnancy awareness, self-reflection, initial abortion decision, disclosure and seeking support, negotiations, final decision, access and information, abortion procedure, and post-abortion experience and care. Determinants of trajectories included three major themes of autonomy in decision-making, access and choice. A meta-analysis of data from 7737 women showed that the proportion of the overall women's involvement in abortion decision-making was 0.86 (95% CI:0.73–0.95, I 2 = 99.5%) and overall partner involvement was 0.48 (95% CI:0.29–0.68, I 2 = 99.6%).

          Interpretation

          Policies and strategies should address women's perceptions of safe abortion socially, legally, and economically, and where appropriate, involvement of male partners in abortion decision-making processes to facilitate safe abortion. Clinical heterogeneity, in which various studies defined “the final decision-maker” differentially, was a limitation of our study.

          Funding

          Nuffield Department of Population Health DPhil Scholarship for PL, University of Oxford, and the Medical Research Council Career Development Award for MN (Grant Ref: MR/P022030/1).

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          Most cited references101

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          Unintended pregnancy and abortion by income, region, and the legal status of abortion: estimates from a comprehensive model for 1990–2019

          Unintended pregnancy and abortion estimates document trends in sexual and reproductive health and autonomy. These estimates inform and motivate investment in global health programmes and policies. Variability in the availability and reliability of data poses challenges for measuring and monitoring trends in unintended pregnancy and abortion. We developed a new statistical model that jointly estimated unintended pregnancy and abortion that aimed to better inform efforts towards global equity in sexual and reproductive health and rights.
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            Convergent and sequential synthesis designs: implications for conducting and reporting systematic reviews of qualitative and quantitative evidence

            Background Systematic reviews of qualitative and quantitative evidence can provide a rich understanding of complex phenomena. This type of review is increasingly popular, has been used to provide a landscape of existing knowledge, and addresses the types of questions not usually covered in reviews relying solely on either quantitative or qualitative evidence. Although several typologies of synthesis designs have been developed, none have been tested on a large sample of reviews. The aim of this review of reviews was to identify and develop a typology of synthesis designs and methods that have been used and to propose strategies for synthesizing qualitative and quantitative evidence. Methods A review of systematic reviews combining qualitative and quantitative evidence was performed. Six databases were searched from inception to December 2014. Reviews were included if they were systematic reviews combining qualitative and quantitative evidence. The included reviews were analyzed according to three concepts of synthesis processes: (a) synthesis methods, (b) sequence of data synthesis, and (c) integration of data and synthesis results. Results A total of 459 reviews were included. The analysis of this literature highlighted a lack of transparency in reporting how evidence was synthesized and a lack of consistency in the terminology used. Two main types of synthesis designs were identified: convergent and sequential synthesis designs. Within the convergent synthesis design, three subtypes were found: (a) data-based convergent synthesis design, where qualitative and quantitative evidence is analyzed together using the same synthesis method, (b) results-based convergent synthesis design, where qualitative and quantitative evidence is analyzed separately using different synthesis methods and results of both syntheses are integrated during a final synthesis, and (c) parallel-results convergent synthesis design consisting of independent syntheses of qualitative and quantitative evidence and an interpretation of the results in the discussion. Conclusions Performing systematic reviews of qualitative and quantitative evidence is challenging because of the multiple synthesis options. The findings provide guidance on how to combine qualitative and quantitative evidence. Also, recommendations are made to improve the conducting and reporting of this type of review.
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              An administrative data merging solution for dealing with missing data in a clinical registry: adaptation from ICD-9 to ICD-10

              Background We have previously described a method for dealing with missing data in a prospective cardiac registry initiative. The method involves merging registry data to corresponding ICD-9-CM administrative data to fill in missing data 'holes'. Here, we describe the process of translating our data merging solution to ICD-10, and then validating its performance. Methods A multi-step translation process was undertaken to produce an ICD-10 algorithm, and merging was then implemented to produce complete datasets for 1995–2001 based on the ICD-9-CM coding algorithm, and for 2002–2005 based on the ICD-10 algorithm. We used cardiac registry data for patients undergoing cardiac catheterization in fiscal years 1995–2005. The corresponding administrative data records were coded in ICD-9-CM for 1995–2001 and in ICD-10 for 2002–2005. The resulting datasets were then evaluated for their ability to predict death at one year. Results The prevalence of the individual clinical risk factors increased gradually across years. There was, however, no evidence of either an abrupt drop or rise in prevalence of any of the risk factors. The performance of the new data merging model was comparable to that of our previously reported methodology: c-statistic = 0.788 (95% CI 0.775, 0.802) for the ICD-10 model versus c-statistic = 0.784 (95% CI 0.780, 0.790) for the ICD-9-CM model. The two models also exhibited similar goodness-of-fit. Conclusion The ICD-10 implementation of our data merging method performs as well as the previously-validated ICD-9-CM method. Such methodological research is an essential prerequisite for research with administrative data now that most health systems are transitioning to ICD-10.
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                Author and article information

                Contributors
                Journal
                eClinicalMedicine
                EClinicalMedicine
                eClinicalMedicine
                Elsevier
                2589-5370
                17 October 2022
                December 2022
                17 October 2022
                : 54
                : 101694
                Affiliations
                [a ]National Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
                [b ]Chelsea and Westminster Hospital, NHS Foundation Trust, London, UK
                [c ]MSI Reproductive Choices, London, UK
                [d ]Ethox Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK
                [e ]Department of Community Health and Behavioural Sciences, School of Public Health, College of Health Sciences, Makerere University, Kampala, Uganda
                [f ]Department of Medical Statistics, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
                Author notes
                [* ]Corresponding author at: National Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington OX3 7LF Oxford, UK. paul.lokubal@ 123456ndph.ox.ac.uk
                Article
                S2589-5370(22)00424-2 101694
                10.1016/j.eclinm.2022.101694
                9579809
                7d21b532-7863-472b-8807-780114ec7353
                © 2022 The Author(s)

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 28 June 2022
                : 21 September 2022
                : 22 September 2022
                Categories
                Articles

                abortion,pregnancy termination,decision-making,abortion trajectories,low- and middle-income countries,mixed-methods,systematic review,meta-analysis

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